Application of weighted correlation network towards predicting onset of aeroelastic instability

2022 ◽  
Author(s):  
Sombuddha Bagchi ◽  
Vishnu R. Unni ◽  
Abhishek Saha
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Chenxing Wu ◽  
Hongwang Song ◽  
Xiaojun Fu ◽  
Shouwei Li ◽  
Tao Jiang

Background. Glioma is the most common and lethal tumor in the central nervous system (CNS). More than 70% of WHO grade II/III gliomas were found to harbor isocitrate dehydrogenase (IDH) mutations which generated targetable metabolic vulnerabilities. Focusing on the metabolic vulnerabilities, some targeted therapies, such as NAMPT, have shown significant effects in preclinical and clinical trials. Methods. We explored the TCGA as well as CGGA database and analyzed the RNA-seq data of lower grade gliomas (LGG) with the method of weighted correlation network analysis (WGCNA). Differential expressed genes were screened, and coexpression relationships were grouped together by performing average linkage hierarchical clustering on the topological overlap. Clinical data were used to conduct Kaplan–Meier analysis. Results. In this study, we identified ACAA2 as a prognostic factor in IDH mutation lower grade glioma with the method of weighted correlation network analysis (WGCNA). The difference of ACAA2 gene expressions between the IDH wild-type (IDH-WT) group and the IDH mutant (IDH-MUT) group suggested that there may be different potential targeted therapies based on the fatty acid metabolic vulnerabilities, which promoted the personalized treatment for LGG patients.


Cells ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 143
Author(s):  
Virginie Dubourg ◽  
Alexander Nolze ◽  
Michael Kopf ◽  
Michael Gekle ◽  
Gerald Schwerdt

Environmental food contaminants constitute a threat to human health. For instance, the globally spread mycotoxin Ochratoxin A (OTA) contributes to chronic kidney damage by affecting proximal tubule cells via unknown mechanisms. We applied a top-down approach to identify relevant toxicological mechanisms of OTA using RNA-sequencing followed by in-depth bioinformatics analysis and experimental validation. Differential expression analyses revealed that OTA led to the regulation of gene expression in kidney human cell lines, including for genes enriched in cell cycle-related pathways, and OTA-induced gap 1 and 2 (G1 and G2) cell-cycle arrests were observed. Weighted correlation network analysis highlighted cyclin dependent kinase 2 (CDK2) as a putative key regulator of this effect. CDK2 was downregulated by OTA exposure, and its overexpression partially blocked the OTA-induced G1 but not G2 cell-cycle arrest. We, therefore, propose CDK2 as one of the key regulators of the G1 cell-cycle arrest induced by low nanomolar concentrations of OTA.


2015 ◽  
Vol 43 (3) ◽  
pp. 1418-1432 ◽  
Author(s):  
Natalia Kunowska ◽  
Maxime Rotival ◽  
Lu Yu ◽  
Jyoti Choudhary ◽  
Niall Dillon

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